How Can Big Data Support Learning Process_ a Case Study in Organization Internal Healthcare Provider

8/12/2019 How Can Big Data Support Learning Process_ a Case Study in Organization Internal Healthcare Provider

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Nowdays Big Data analytics is used in many aspects of organisations. This paper

discuss about how big data is used to improve learning process and support learning

organization. This paper take case of Yakes Telkom as PT. Telkom internal healthcare

provider that has 403 of staff separately in 950 clinics all-over Indonesia. Yakes Telkom

has to service more less 150.000 people, including employees, pensions and their

dependents. Yakes has online medical record system that integrate all medical data from

all clinics. Having huge medical records from its patients, could be used to improve

quality of care that they provide. By sharing and analyzing healthcare information,

physicians can identify the best treatments for their patients and do service excellent.

Comprehensive analytics can also give more correlated view of cost and quality of both

in healthcare delivery and administrative process. Furthermore, it could be reduce

healthcare expenditure of the organization itself.

Keywords:

Data is one of important asset had by organization. Data is commonly used to

help decision making process in any level of management. Data is also basic for creating

knowledge. It then used by organization to improve and innovate process or product.

Digitalization almost all data in organization make explotion number of data. Beside

increasing the volume, technology development also enable organization to process and

analyze variation of data, not only structured data but also unstructured data. Organization

should also consider about its velocity and veracity to optimize that large amount of data,

either from outside or inside organizitation. Now days, its called as Big Data.

Data and information that have pattern can form knowledge. According to Delphi

But now in the Big Data era and information technology development, organizations can

have knowledge not only from their employees but also from their consumers, partners,

and other sources outside them.


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Big Data could improve the way organizations do businesses even generate a

new business. According to research by McAfee and Brynjolfsson from MIT, companies

that inject big data and analytics into their operation show productivity rates and

. Big Data

by Garvin (1993) in Jashpara (2004); systematic problem solving, experimentation with

new approaches, learning from their own experience and past history, learning from

the experiences and best practices of others, and transferring knowledge quickly and

This paper propose a concept of Big Data analytics to support learning process

in organization especially healthcare service provider. In Indonesia, a big corporate, like

PT. Telkom Indonesia.Tbk, commonly has internal healthcare provider which organize

healthcare services for all employees, pensions, and their families. With better learning

process, it is expected can improve the services and claim-cost. This paper take a casestudy from Yakes Telkom as internal healthcare provider of Telkom.

Relation between pieces of data can form information. Information that processed

further can become knowledge when one realize and understand the pattern relation

among data and information and their implication[4]. Knowledge is one of important

asset in an organization. Therefore, organization should optimize knowledge to support

the development of product, process, or services.

Information technology has been used for supporting knowledge management

and integrative application. Integrative applications take the form of structured

databases that allow employees to store and retrieve information on past projects, expert

Interactive applications take the form of email, desktop conferencing, and discussion

forums allowing for interactions with other staff and the garnering of their views and

experiences regardless of physical location.

Knowledge management and learning organization are two terms that related

knowledge: knowledge being the stuff (or content) that the organization possesses,

and learning being the process whereby it acquires this stuff. Therefore, information

technology used in knowledge management can also be usefull for supporting learning

organization.


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organizations where people

continually expand their capacity to create the results they truly desire, where new and expansive

learning to see the whole together (Jashpara, 2004). Almost same with Senge, Pedler,

an organization that

its strategic goals (Yang, 2004). While Garvin (1993) said, a learning organization is an

conclude that in a learning orgnization, employees are encouraged and facilitated to

upgrade their knowledges and skills by improve their learning capacity in order to meet

organization strategic goals.

Senge (Senge, 2004):1. System thinking. A framework for seeing interrelationships rather than things,

for seeing patterns of change rather than static snapshots. System thinking is a

discipline for seing wholes.

2. Personal mastery. It is the of personal growth and learning. People with high levels

of personal mastery are continually expanding their ability to create the results in

life they truly seek. Organizations learn only through individuals who learn.

3. Mental model. Assumptions, generalizations, or even pictures or images that

mental models promises to be a major breakthrough for building learning

organizations.4. Building shared vision. A vision that many people are truly commited to, because it

because it provides the focus and energy for learning.

5. Team learning. When teams are truly learning, not only are they producing

extraordinary results but the individual members are growing more rapidly than

could have occured otherwise.

learning organization in order the process to succeed:

1. Mission and vision. A widely shared and understood mission enables staff at all

levels to develop their skills and capabilities, take reponsibilities and contribute toorganizational performance

2. Leadership. Empowers employees, encourages an experimenting culture, rewards

learning, supports innovative suggestions and frequently generates learning

opportunities on-the-job

3. Transfer of Knowledge. Learning form past failures makes knowledge explicit and

enables its transfer from individual to organizational level


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4. Teamwork and co-operation. Diversity of team members knowledge and

backgrounds stimulates dialogue, brainstorming and team problem solving

5. Experimenting culture. Sets aside resources for employees to enagage in creative

pet projects, develops rewarding mechanisms for those that excel in this area and

tolerates errors.

main activities:

systematic problem solving,

experimentation with new approaches,

learning from their own experience and past history,

learning from the experiences and best practices of others, and

a.

Big data refers to datasets whose size is beyond the ability of typical database

software tools to capture, store, manage, and analyze (McKinsey, 2011). Every

data that offer transformational potential to create value an have implications for

how organizations will have to be designed, organized, and managed.

1. Creating tansparency. Making big data more easily accessible to relevant

stakeholders in a timely manner.

2. Enabling experimentation to discover needs, expose variability, and improve

performace. Organizations can collect more accurate and detailed performance

data (in real or near real time) on everything as they create and store more

transactional data in digital form.

3. Segmenting populations to customize actions. Big data allows organizations to

to meet those needs.

4. Replacing/supporting human decision making with automated algorithms.

In some cases, decisions will not necessarily be automated but augmanted by

analyzing huge, entire datasets using big data techniques and technologies.

5. Innovating new business models, products, and services. Big data enables

companies to create new products and services, enhance existing ones, and

invent entirely new business models.

Big Data analytics is developed from data analytics dicipline which has been used

for a long time ago for helping decision making in organization. Data analytics was

used structured data with ETL (Extract, Transform, and Load) process. Some its

popular applications are business intelligence, data mining, and other OLAP (Online

Analytical Process) systems.

There are four Vs that characterize Big Data (Sathi, 2012):


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1. Volume. With automation and digitalize data, organizations now have a

huge amount of data that come from within the corporation and outside the

organization.

2. Velocity. There two aspects of velocity, throuhgput of data (data moving in the

pipes) and latency (using data in motion)

3. Variety. The source data includes unstructured text, sound, and video in addition

to structured data.

4. Veracity. Veracity represents both the credibility of the data source as well as the

suitability of the data for the target audience.

b. Big Data Application in Healthcare

to the growth of big data. Image data in the form of X-rays, CT and other scans

dominate data storage volumes in healthcare. While a singe page of records can

total a kilobyte, a single image can require 20 tp 200 megabutes or more to store

(McKinsey, 2011).

Healthcare organization usually has multiple stakeholders, including pharmaceutical

and medical products industries, providers, insurance agencies and patients. Each

generates pools of data, but they have typically remained unconnected from each

health care domain; pharmaceutical R&D data, clinical data, activity (claims) and

cost data, and patient behavior and sentiment data. Using big data analysis from

productivity enhancement (McKinsey, 2011).

According to McKinsey Global Institute (2011) in healthcare industry, Big Data

could be used to:

1. Comparative effectiveness research

2. Clinical decision support systems

3. Transparency about medical data

4. Remote patient monitoring

5.

6. Automated payment systems

7. Health economics and outcomes research and performance-based pricing plans

Creating new business models: Online platforms and communities

9. And supporting public health program.

This research uses qualitative method and exploratory approach. Its a case study

of an internal organization of a healthcare provider. Primary data is from interview with

head of service division of Yakes-Telkom. Secondary data consists of internal documents

and internet references. The data was analyze by comparing study with another cases in

US healthcase services to formulate a conceptual strategies of learning process using Big


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Data in the case study object.

PT. Telekomunikasi Indonesia, Tbk (Telkom) is one of the biggest state-owned

enterprise in telecommunication industry. Since 1965, healthcare services had given for

get restitution for they health care fee from the government through their institution.

Telkom (Yakes-Telkom) was founded as separated entity from Telkom, following the

policy to become go public company. Since 2000, all health care management, in regional

devision, support devision, and some subsidiaries of Telkom have been managed

byYakes-Telkom.

Yakes-Telkom has mission to becoming the best healthcare service provider in

Indonesia. To support its mission, Yakes-Telkom has establishes some strategies and

policies. Some of them, that related to this paper, are increasing healthcare services and

controlling expenditures. Until mid-year 2013, Yakes-Telkom has 403 employees, consits

of medical and non-medical staff, spread in 950 clinics operated in 7 regions in Indonesia.

Healthcare services provided inlcuding medical laboratorium, pharmacy, optic, general

check-up, and some specialist. Yakes also has six internal laboratoriums under Rasapala

(Yakes subsidiaries) management. Yakes-Telkom has around 120.000 members from

Telkom Group (including employees, pensions and their families) and around 30.000

members from Telkom subsidiaries.

Yakes-Telkom has online medical record system that integrate all medical data

of Yakes members. The system record patients personal data, treatment duration,

healthcare expenditures, hospitality history, and drugs records. With this system,

patients can get treatment from any clinic with any doctor without worry about their

medical data. All data from internal clinic (organized by Yakes) will be uploaded to

medical record system by each doctors. If they take medical treatment from partner

hospital, data will be input by staff when employees or pensions ask for restitutions.

They should give proof of payment and medical resume from the partner hospital. From

all clinics, it could reach 2560 transactions a day.

To reach it goals, Yakes-Telkom has a lot of programs devided in preventive,

currative, and rehabilitative programs. Preventive programs consist of health club,

healthiest family award, health-life paradigm, annual medical check-up, monthlymonitoring (for employees and pensions grouped as unhealthy condition). Currative

programs including medical treatment in clinic and hospital. Another program is

establishing Telkoms dugs list or Daftar Obat Telkom (DOT) for employees and pensions

of Telkom. DOT is list of drugs and pharmacy materials that have selected by medical

proof, save and efective. This program has objectives for drug use standardization,


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Beside programs for healthcare services, Yakes also has programs to increase

cost by maximizing factory discount, reward and punishment, decreasing margin of

pharmacy and hospital, drugs formulation, and regulation of healthcare facility.

Yakes-Telkom has a large number of data that can be optimized to improve its

clinical data, patients behavior data, and activity and cost data. Each data pools consists

of some data sets that come from different elements. These are the detail of data pools

that can be formed by Yakes.

1. Clinical data.

Example datasets: electronic medical record, medical image, drugs list standard

Sources: Yakes clinics, partner hospitals

2. Patients behavior data

Example datasets: exercise data, patients behavior and preferences

Source: Patients

3. Activity and cost data

Example datasets: utilization of care, cost estimation

Sources: Yakes clinics, partner hospitals

Figure 1.

With those data pools, Yakes can implement some Big Data solution are to do

improvement for services and processes. These are some potential improvement from


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big data analytics implementation, adopted from Mc Kinsey Global Institute analysis

(McKinsey, 2011).

1. Comparative effectiveness research.

comprehensive patient and outcome data to compare the effectiveness of various

interventions. This solution can be supported by clinical data and patients behavior

data

2. Clinical decision support systems.

of operations. This solution can be supported by clinical data and activity and cost

data.

3. Transparency about medical data.

The goal is to identify and analyze sources of variability and waste in clinical

processes and then optimize processes. This can be supported by clinical data and

activity and cost data.

4. Remote patient monitoring.

Collecting data from remote patient monitoring for chronically ill patients and

analyzing the resulting data to monitor adherence (determining if patients are

actually doing what was prescribed) and to improve future drug and treatment

options. This can be supported by patients behavior data.

5.

changes. This can be supported by clinical data and patients behavior data.

6. Automated pricing systems.

Implementing automated systems for fraud detection and checking the accuracy

and consistency of patients claims. This can be supported by activity and cost data.

7. Online platforms and communities.

Forum for individuals can share their experience as patients in the system, or a forum

for physicians to share their medical insights. This can be supported by patients

behavior data

This table below shows how those big data solution could be used in each

learning process.

1

2

3

5

6

7

No

from own

from


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Table 1.Mapping of Big Data Solution and Learning Process

Next step, we mapped Big Data Solutions above (from Tabel 1) to Yakes Progams.

by related programs.

Increasing

healthcare services

Controlling

expenditures

health club V 4, 7

health family awards V 4, 7

health-life paradigm V 4, 7

annual medical check-up V 1, 5

monthly monitoring V 4, 5

currative treatment V 1, 2, 3

drug lists (DOT) V V 1, 2, 6

medical treatment standardization V V 2, 3

reducing claim cost V 6

reward and punishment V V 2decreasing margin of pharmacy & hospital V 6

drugs formulation standard V 2, 6

regulation of healthcare facility V 2

Big Data

Solution(s)

Yakes' Programs

Tabel 2.

In case of Yakes Telkom, those solution can also help Yakes programs to increase

healthcare services and control expenditures. This research still has many weakneasses.

For further research, we recommend to add more data and more detail discussion about

big data solutions that could be implemented in organization.

[1 ] Hayes, Niall. 2011. Information Technology and Possibilities for Knowledge Sharing.

Handbook of Organizational Learning & Knowledge Management, SecondEdition. United Kingdom. John Willey & Sons.

[2] Jashpara, Ashok. 2004. Knowledge Management, An integrated Approach. PrenticeHall. Pearson Education

[3] Keidrowski, P.Jay. 2006. Quantitative assessment of a Senge learning organization

Group Publishing Limited.

[4] McAfee, Andrew and Erik Brynjolfsson. 2012. Big Data: The Management Revolution.Harvard Business Review. October 2012.

[5] McKinsey Global Institue. 2011. Big data: The next frontier for innovation, competitiion,and productivity. McKinsey & Company.

[6] Sathi, Arvind. 2012. Big Data Analytics. Disruptive Technologies for Changing the


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Game. MC Press Online, LLC

[7] Senge, Peter M.. 2004. Fifth Dicipline: The Art & practice of Learning Organization.New York: Doubleday.

Learning and Knowledge Management. Handbook of Organizational Learning &Knowledge Management, Second Edition. United Kingdom. John Willey & Sons.

Foundation. Jakarta

[10] Vassalou, Leda. 2001. The learning organization in health-care services: theory andpractice. Journal of European Industrial Training. MCB university Press [ISSN0309-0590]

[11] Wahyono, Teguh. 2013. Pendirian dan Pengelolaan Yayasan Kesehatan PegawaiTelkom. Yakes-Telkom.

[12] Yang, baiyin., Watkins, E. KAren, Marsick, Victoria J.2004. Construct of the LearningOrganization: Dimensions, Measurement, and Validation. Human Resource

Development Quarterly, vol. 15, no. 1, Spring 2004. Wiley Periodicals, Inc

How Can Big Data Support Learning Process_ a Case Study in Organization Internal Healthcare Provider

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